{"id":"https://openalex.org/W3043693934","doi":"https://doi.org/10.26599/bdma.2020.9020001","title":"Error data analytics on RSS range-based localization","display_name":"Error data analytics on RSS range-based localization","publication_year":2020,"publication_date":"2020-07-16","ids":{"openalex":"https://openalex.org/W3043693934","doi":"https://doi.org/10.26599/bdma.2020.9020001","mag":"3043693934"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2020.9020001","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2020.9020001","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9142126/09142149.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654","2097-406X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ieeexplore.ieee.org/ielx7/8254253/9142126/09142149.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025361199","display_name":"Shuhui Yang","orcid":"https://orcid.org/0000-0002-1263-433X"},"institutions":[{"id":"https://openalex.org/I117015748","display_name":"Purdue University Northwest","ror":"https://ror.org/04keq6987","country_code":"US","type":"education","lineage":["https://openalex.org/I117015748"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuhui Yang","raw_affiliation_strings":["Department of Mathematics, Statistics, and Computer Science, Purdue University Northwest, Hammond, IN 46323, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Statistics, and Computer Science, Purdue University Northwest, Hammond, IN 46323, USA","institution_ids":["https://openalex.org/I117015748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050019834","display_name":"Zimu Yuan","orcid":"https://orcid.org/0000-0002-9494-7478"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zimu Yuan","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100864, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100864, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100318448","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-4242-1615"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100864, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100864, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1104,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77461386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"3","issue":"3","first_page":"155","last_page":"170"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9398000240325928,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9097999930381775,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.9767218828201294},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7341356873512268},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.698614239692688},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.6203089952468872},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5503931045532227},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5375162959098816},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5095548629760742},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4775160849094391},{"id":"https://openalex.org/keywords/observational-error","display_name":"Observational error","score":0.47535842657089233},{"id":"https://openalex.org/keywords/measurement-uncertainty","display_name":"Measurement uncertainty","score":0.45777130126953125},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.43712154030799866},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.43173345923423767},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20104938745498657},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1868038773536682},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.15093573927879333},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07332596182823181}],"concepts":[{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.9767218828201294},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7341356873512268},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.698614239692688},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.6203089952468872},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5503931045532227},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5375162959098816},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5095548629760742},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4775160849094391},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.47535842657089233},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.45777130126953125},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.43712154030799866},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.43173345923423767},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20104938745498657},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1868038773536682},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.15093573927879333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07332596182823181},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/bdma.2020.9020001","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2020.9020001","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9142126/09142149.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654","2097-406X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ea9ee9b718f74333ac4e7a56bf1560bc","is_oa":true,"landing_page_url":"https://doaj.org/article/ea9ee9b718f74333ac4e7a56bf1560bc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 3, Iss 3, Pp 155-170 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2020.9020001","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2020.9020001","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9142126/09142149.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654","2097-406X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1566135399","https://openalex.org/W1608899808","https://openalex.org/W1903227812","https://openalex.org/W1964865687","https://openalex.org/W1965006965","https://openalex.org/W1965919406","https://openalex.org/W1974755780","https://openalex.org/W2001984538","https://openalex.org/W2005189835","https://openalex.org/W2009284097","https://openalex.org/W2038357359","https://openalex.org/W2052550038","https://openalex.org/W2054279494","https://openalex.org/W2054405892","https://openalex.org/W2061570754","https://openalex.org/W2080780898","https://openalex.org/W2082715409","https://openalex.org/W2100456966","https://openalex.org/W2101317465","https://openalex.org/W2105364947","https://openalex.org/W2105738738","https://openalex.org/W2106048721","https://openalex.org/W2114351513","https://openalex.org/W2114646535","https://openalex.org/W2117521997","https://openalex.org/W2121564285","https://openalex.org/W2124178852","https://openalex.org/W2129565682","https://openalex.org/W2140708977","https://openalex.org/W2150151472","https://openalex.org/W2161859912","https://openalex.org/W2165295831","https://openalex.org/W2211741815","https://openalex.org/W2254654304","https://openalex.org/W2341433667","https://openalex.org/W2364574607","https://openalex.org/W2394576961","https://openalex.org/W2408272418","https://openalex.org/W2544515865","https://openalex.org/W2979172579","https://openalex.org/W4206076131","https://openalex.org/W4235357343"],"related_works":["https://openalex.org/W2903691317","https://openalex.org/W4224323762","https://openalex.org/W2099208041","https://openalex.org/W2220451197","https://openalex.org/W2370122455","https://openalex.org/W1600397729","https://openalex.org/W1825457241","https://openalex.org/W2360832559","https://openalex.org/W4284698423","https://openalex.org/W1989588780"],"abstract_inverted_index":{"The":[0,81,160],"quality":[1],"of":[2,10,83,87,136,162,186],"measurement":[3,21,53,99,109],"data":[4,28,65,177],"is":[5,29,48,93,118,158],"critical":[6,30],"to":[7,18,31,36,69,111,120,205],"the":[8,19,23,26,38,84,88,94,121,129,134,143,148,152,184,191,195],"accuracy":[9,86,135,154,185],"both":[11],"outdoor":[12],"and":[13,35,51,142,155,182,199],"indoor":[14,42],"localization":[15,33,60,67,91,138,153,175,188,208],"methods.":[16],"Due":[17],"inevitable":[20],"error,":[22],"analytics":[24,144,197],"on":[25,97,194],"error":[27,117,176],"evaluate":[32],"methods":[34,92,139],"find":[37,112],"effective":[39],"ones.":[40],"For":[41],"localization,":[43],"Received":[44],"Signal":[45],"Strength":[46],"(RSS)":[47],"a":[49,71,107,171],"convenient":[50],"low-cost":[52],"that":[54,74,132,146],"has":[55,165],"been":[56],"adopted":[57],"in":[58],"many":[59],"approaches.":[61],"However,":[62],"using":[63],"RSS":[64,98],"for":[66,174],"needs":[68],"solve":[70],"fundamental":[72],"problem,":[73],"is,":[75],"how":[76],"accurate":[77],"are":[78,140],"these":[79,156],"methods?":[80],"reason":[82],"low":[85],"current":[89,207],"RSS-based":[90,137],"oversimplified":[95],"analysis":[96],"data.":[100],"In":[101],"this":[102],"proposed":[103],"work,":[104],"we":[105,169],"adopt":[106],"generalized":[108],"model":[110],"optimal":[113],"estimators":[114],"whose":[115],"estimated":[116],"equal":[119],"Cram\u00e9r-Rao":[122],"Lower":[123],"Bound":[124],"(CRLB).":[125],"Through":[126],"mathematical":[127],"techniques,":[128],"key":[130],"factors":[131,157],"affect":[133],"revealed,":[141],"expression":[145,173,198],"discloses":[147],"proportional":[149],"relationship":[150],"between":[151],"derived.":[159],"significance":[161],"our":[163],"discovery":[164],"two":[166],"folds:":[167],"First,":[168],"present":[170],"general":[172,196],"analytics,":[178],"which":[179],"can":[180,202],"explain":[181],"predict":[183],"range-based":[187],"algorithms;":[189],"second,":[190],"further":[192],"study":[193],"its":[200],"minimum":[201],"be":[203],"used":[204],"optimize":[206],"algorithms.":[209]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
